You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
82 lines
1.9 KiB
82 lines
1.9 KiB
7 years ago
|
import os
|
||
6 years ago
|
import sys
|
||
|
|
||
|
sys.path.append('../')
|
||
7 years ago
|
from core.dann import train_dann
|
||
|
from core.test import eval
|
||
|
from models.model import AlexModel
|
||
|
|
||
6 years ago
|
from utils.utils import get_data_loader, init_model, init_random_seed
|
||
7 years ago
|
|
||
7 years ago
|
|
||
|
class Config(object):
|
||
|
# params for path
|
||
|
dataset_root = os.path.expanduser(os.path.join('~', 'Datasets'))
|
||
6 years ago
|
model_root = os.path.expanduser(
|
||
|
os.path.join('~', 'Models', 'pytorch-DANN'))
|
||
7 years ago
|
|
||
|
# params for datasets and data loader
|
||
7 years ago
|
batch_size = 32
|
||
7 years ago
|
|
||
|
# params for source dataset
|
||
|
src_dataset = "amazon31"
|
||
|
src_model_trained = True
|
||
6 years ago
|
src_classifier_restore = os.path.join(
|
||
|
model_root, src_dataset + '-source-classifier-final.pt')
|
||
7 years ago
|
|
||
|
# params for target dataset
|
||
6 years ago
|
tgt_dataset = "webcam10"
|
||
7 years ago
|
tgt_model_trained = True
|
||
6 years ago
|
dann_restore = os.path.join(
|
||
|
model_root, src_dataset + '-' + tgt_dataset + '-dann-final.pt')
|
||
7 years ago
|
|
||
|
# params for pretrain
|
||
|
num_epochs_src = 100
|
||
6 years ago
|
log_step_src = 5
|
||
7 years ago
|
save_step_src = 50
|
||
|
eval_step_src = 20
|
||
|
|
||
|
# params for training dann
|
||
|
|
||
6 years ago
|
# for office
|
||
|
num_epochs = 1000
|
||
6 years ago
|
log_step = 10 # iters
|
||
7 years ago
|
save_step = 500
|
||
6 years ago
|
eval_step = 5 # epochs
|
||
7 years ago
|
|
||
|
manual_seed = 8888
|
||
|
alpha = 0
|
||
|
|
||
|
# params for optimizing models
|
||
|
lr = 2e-4
|
||
|
|
||
6 years ago
|
|
||
7 years ago
|
params = Config()
|
||
|
|
||
7 years ago
|
# init random seed
|
||
|
init_random_seed(params.manual_seed)
|
||
|
|
||
|
# load dataset
|
||
6 years ago
|
src_data_loader = get_data_loader(
|
||
|
params.src_dataset, params.dataset_root, params.batch_size)
|
||
|
tgt_data_loader = get_data_loader(
|
||
|
params.tgt_dataset, params.dataset_root, params.batch_size)
|
||
7 years ago
|
|
||
|
# load dann model
|
||
7 years ago
|
dann = init_model(net=AlexModel(), restore=None)
|
||
7 years ago
|
|
||
|
# train dann model
|
||
|
print("Start training dann model.")
|
||
|
|
||
|
if not (dann.restored and params.dann_restore):
|
||
6 years ago
|
dann = train_dann(dann, params, src_data_loader,
|
||
|
tgt_data_loader, tgt_data_loader)
|
||
7 years ago
|
|
||
|
# eval dann model
|
||
|
print("Evaluating dann for source domain")
|
||
|
eval(dann, src_data_loader)
|
||
|
print("Evaluating dann for target domain")
|
||
|
eval(dann, tgt_data_loader)
|
||
|
|
||
6 years ago
|
print('done')
|